Data & Analytics
Turn your data into decisions.
You've probably said it: «we have the data but we don't know what to do with it». That's normal, 90% of companies are in that position. Data is there but scattered, poorly modeled, invisible to people who should see it.
We build solid, documented, governed data platforms: ETL/ELT pipelines, data warehouses, self-service dashboards. Goal: every decision-maker has the right data at the right time.
What we set up
- ETL/ELT pipelines
- Ingestion from your CRM, ERP, SaaS apps, SQL databases, flat files. Apache Airflow, dbt, Fivetran, Meltano.
- Data warehouse
- Dimensional or Data Vault modeling. Snowflake, BigQuery, Databricks or ClickHouse depending on volumes.
- Business dashboards
- Self-service dashboards for execs, sales, ops. Metabase, Looker Studio, Power BI, Tableau.
- Real-time analytics
- Streaming with Kafka + ClickHouse for second-by-second dashboards. Live anomaly detection.
- Data quality & catalog
- Great Expectations tests, quality monitoring, data catalog (DataHub, Amundsen). Every table has an owner.
- Governance & compliance
- Anonymisation, pseudonymisation, fine-grained access control, GDPR and CNDP traceability.
Real-world use cases
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Retail · 40 stores
360° sales view
Merging POS, e-commerce, marketplaces, inventory. Exec dashboard browsable every morning in 3 clicks.
80% data-driven decisions
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Fintech
Real-time fraud scoring
Kafka + ClickHouse scoring every transaction in < 50ms. Escalation to analysts past threshold.
-73% fraud
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Manufacturing
Factory dashboard
IoT sensors → Kafka → real-time dashboard for maintenance team. Predictive downtime detection.
+22% OEE
How we work
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01
Data audit
Source inventory, business KPI mapping, gap identification.
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02
Architecture & PoC
Data platform design, PoC on 1-2 concrete use cases in 4 weeks.
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03
Industrialisation
Pipelines, DWH modeling, dashboards, documentation.
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04
Adoption & evolution
Analyst and business training. Quarterly usage review. New dashboards as needs arise.
Our data stack
Snowflake, BigQuery, Databricks, ClickHouse, Apache Airflow, dbt, Kafka, Apache Spark, Metabase, Looker Studio, Power BI, Tableau, DataHub.
Frequently asked questions
Where to start from zero?
1 to 3 critical business KPIs. Identify sources, ship an MVP data platform on those KPIs in 6-8 weeks, roll out dashboards. Then extend.
Which BI tool do you recommend?
Metabase to start (open-source, free, simple). Looker Studio if on GCP. Power BI if your company is Microsoft. Tableau for highly demanding visualisation.
On-premise or cloud storage?
Cloud by default (Snowflake, BigQuery) for simplicity, elasticity and cost. On-premise or sovereign cloud for strong regulatory constraints.
How do you handle GDPR / CNDP compliance?
Anonymisation / pseudonymisation at ingestion, fine-grained role-based access, access traceability, DPA signed with each subprocessor.
How much does a data platform cost?
SME: €5-20k setup + €500-2000/mo. Mid-market: €30-80k + €3-15k/mo.
How long until first results?
First useful dashboard: 4-6 weeks. Full platform: 3-6 months. We work in short sprints so you see value from the first months.
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